Pairwise interactions are fundamental to information theory's development of
input-output (“two-port”) communication channels [1]}. As such,
they provide a primary statistical tool that, as we show, makes it possible to
infer the underlying influences among individuals. To obtain maximum insight
into the mechanisms underlying multi-agent systems, the following focuses on
decomposing transfer entropy and time-delayed mutual information into Ref.
[2]}'s three different fundamental modes of information
flow—termed intrinsic, shared, and synergistic
information flows. The results demonstrate how the decomposed elemental
information flows shed light on the influences that drive leader-follower
relationships.
